This paper proposes the nonlinear direct data-driven control from theoretical analysis and practical engineering,i.e.,unmanned aerial vehicle(UAV)formation flight system.Firstly,from the theoretical point of view,cons...This paper proposes the nonlinear direct data-driven control from theoretical analysis and practical engineering,i.e.,unmanned aerial vehicle(UAV)formation flight system.Firstly,from the theoretical point of view,consider one nonlinear closedloop system with a nonlinear plant and nonlinear feed-forward controller simultaneously.To avoid the complex identification process for that nonlinear plant,a nonlinear direct data-driven control strategy is proposed to design that nonlinear feed-forward controller only through the input-output measured data sequence directly,whose detailed explicit forms are model inverse method and approximated analysis method.Secondly,from the practical point of view,after reviewing the UAV formation flight system,nonlinear direct data-driven control is applied in designing the formation controller,so that the followers can track the leader’s desired trajectory during one small time instant only through solving one data fitting problem.Since most natural phenomena have nonlinear properties,the direct method must be the better one.Corresponding system identification and control algorithms are required to be proposed for those nonlinear systems,and the direct nonlinear controller design is the purpose of this paper.展开更多
Enhancing the stability and performance of practical control systems in the presence of nonlinearity,time delay,and uncertainty remains a significant challenge.Particularly,a class of strict-feedback nonlinear uncerta...Enhancing the stability and performance of practical control systems in the presence of nonlinearity,time delay,and uncertainty remains a significant challenge.Particularly,a class of strict-feedback nonlinear uncertain systems characterized by unknown control directions and time-varying input delay lacks comprehensive solutions.In this paper,we propose an observerbased adaptive tracking controller to address this gap.Neural networks are utilized to handle uncertainty,and a unique coordinate transformation is employed to untangle the coupling between input delay and unknown control directions.Subsequently,a new auxiliary signal counters the impact of time-varying input delay,while a Nussbaum function is introduced to solve the problem of unknown control directions.The leverage of an advanced dynamic surface control technique avoids the“complexity explosion”and reduces boundary layer errors.Synthesizing these techniques ensures that all the closed-loop signals are semi-globally uniformly ultimately bounded(SGUUB),and the tracking error converges to a small region around the origin by selecting suitable parameters.Simulation examples are provided to demonstrate the feasibility of the proposed approach.展开更多
Distributed drive electric vehicles(DDEVs)endow the ability to improve vehicle stability performance through direct yaw-moment control(DYC).However,the nonlinear characteristics pose a great challenge to vehicle dynam...Distributed drive electric vehicles(DDEVs)endow the ability to improve vehicle stability performance through direct yaw-moment control(DYC).However,the nonlinear characteristics pose a great challenge to vehicle dynamics control.For this purpose,this paper studies the DYC through the Takagi-Sugeno(T-S)fuzzy-based model predictive control to deal with the nonlinear challenge.First,a T-S fuzzy-based vehicle dynamics model is established to describe the time-varying tire cornering stiffness and vehicle speeds,and thus the uncertain parameters can be represented by the norm-bounded uncertainties.Then,a robust model predictive control(MPC)is developed to guarantee vehicle handling stability.A feasible solution can be obtained through a set of linear matrix inequalities(LMIs).Finally,the tests are conducted by the Carsim/Simulink joint platform to verify the proposed method.The comparative results show that the proposed strategy can effectively guarantee the vehicle’s lateral stability while handling the nonlinear challenge.展开更多
Permanent magnet synchronous motor(PMSM)is widely used in alternating current servo systems as it provides high eficiency,high power density,and a wide speed regulation range.The servo system is placing higher demands...Permanent magnet synchronous motor(PMSM)is widely used in alternating current servo systems as it provides high eficiency,high power density,and a wide speed regulation range.The servo system is placing higher demands on its control performance.The model predictive control(MPC)algorithm is emerging as a potential high-performance motor control algorithm due to its capability of handling multiple-input and multipleoutput variables and imposed constraints.For the MPC used in the PMSM control process,there is a nonlinear disturbance caused by the change of electromagnetic parameters or load disturbance that may lead to a mismatch between the nominal model and the controlled object,which causes the prediction error and thus affects the dynamic stability of the control system.This paper proposes a data-driven MPC strategy in which the historical data in an appropriate range are utilized to eliminate the impact of parameter mismatch and further improve the control performance.The stability of the proposed algorithm is proved as the simulation demonstrates the feasibility.Compared with the classical MPC strategy,the superiority of the algorithm has also been verified.展开更多
The ability of cyborg locusts to achieve directional movement in complex outdoor environments is critical for search and rescue missions.Currently,there is a lack of research on motion control for cyborg locusts in ou...The ability of cyborg locusts to achieve directional movement in complex outdoor environments is critical for search and rescue missions.Currently,there is a lack of research on motion control for cyborg locusts in outdoor settings.In this study,we developed cyborg locusts capable of performing directional locomotion in intricate outdoor environments,including jumping over obstacles,climbing slopes,traversing narrow pipelines,and accurately reaching predetermined targets along specified routes.We designed a miniature electrical backpack(10 mm×10 mm,0.75 g)capable of receiving stimulus parameters(frequency,duty ratio,and stimulation time)via Bluetooth commands from mobile phones.Electrical stimulation of locust sensory organs,such as the antennae and cercus,induced turning and jumping behaviors.Experi-mental testing of locust movement control was conducted under outdoor conditions with a short electrical stimulation interval.Results showed a positive correlation between locust turning angles and electrical stimulation parameters within a specified range,with an average jumping height exceeding 10 cm.Additionally,the success rate of locust turning and jumping behaviors correlated positively with the interval time between electrical stimulations.Adjusting these intervals during forward crawling phases increased the likelihood of the locusts jumping again.In conclusion,this study success-fully achieved directional locomotion control of cyborg locusts outdoors,providing insights and references for advancing search and rescue capabilities.展开更多
The nanofluid-based direct absorption solar collector(NDASC)ensures that solar radiation passing through the tube wall is directly absorbed by the nanofluid,reducing thermal resistance in the energy transfer process.H...The nanofluid-based direct absorption solar collector(NDASC)ensures that solar radiation passing through the tube wall is directly absorbed by the nanofluid,reducing thermal resistance in the energy transfer process.However,further exploration is required to suppress the outward thermal losses from the nanofluid at high temperatures.Herein,this paper proposes a novel NDASC in which the outer surface of the collector tube is covered with functional coatings and a three-dimensional computational fluid dynamics model is established to study the energy flow distributions on the collector within the temperature range of 400-600 K.When the nanofluid’s absorption coefficient reaches 80 m^(-1),the NDASC shows the optimal thermal performance,and the NDASC with local Sn-In_(2)O_(3) coating achieves a 7.8% improvement in thermal efficiency at 400 K compared to the original NDASC.Furthermore,hybrid coatings with Sn In_(2)O_(3)/WTi-Al_(2)O_(3) are explored,and the optimal coverage angles are determined.The NDASC with such coatings shows a 10.22%-17.9% increase in thermal efficiency compared to the original NDASC and a 7.6%-19.5% increase compared to the traditional surface-type solar collectors,demonstrating the effectiveness of the proposed energy flow control strategy for DASCs.展开更多
Direct Thrust Control(DTC) is effective in dealing with the mismatch between thrust and rotor speed in traditional engine control. Among the DTC architecture, model-based thrust estimation method has less arithmetic c...Direct Thrust Control(DTC) is effective in dealing with the mismatch between thrust and rotor speed in traditional engine control. Among the DTC architecture, model-based thrust estimation method has less arithmetic consumption and better real-time performance. In this paper,a direct thrust controller design approach for gas turbine engine based on parameter dependent model is proposed. In order to ensure the stability of DTC control system based on parameter dependent model, there are usually conservatism detects. For the purpose of reducing the conservatism in the solution process of filter and controller, an Equilibrium Manifold Expansion(EME) model with bounded parameter variation of engine is established. The design conditions of Kalman filter for discrete-time EME system are introduced, and the proposed conditions have a certain suppression effect on the input noise of the system with bounded parameter variation.The engine thrust estimator stability and H∞filtering problems are solved by the polytopic quadratic Lyapunov function based on the Linear Matrix Inequalities(LMIs). To meet the performance requirements of thrust control, the Grey Wolf Optimization(GWO) algorithm is applied to optimize the PID control parameters. The proposed method is verified on a Hardware-in-Loop(HIL) platform. The simulation results demonstrate that the DTC framework can ensure the stability of engine closed-loop system in large range deviation tests. The filter and controller solution method considering the parameter variation boundary can obtain a solution that makes the system have better performance parameters. Moreover, the proposed filter has better thrust estimation performance than the traditional Kalman filter under the condition of sensor noise. Compared with Augmented Linear Quadratic Regulator(ALQR) controller, the PID controller optimized by GWO has a faster response in simulation.展开更多
Laser directed energy deposition(LDED)is an emerging branch of metal-based additive manufacturing(AM)processes,offering unprecedented capabilities for high-performance fabrication with complex geometries and near-net ...Laser directed energy deposition(LDED)is an emerging branch of metal-based additive manufacturing(AM)processes,offering unprecedented capabilities for high-performance fabrication with complex geometries and near-net shapes.This technology is gathering increasing attention from industries such as biomedical,automotive,and aerospace.However,achieving consistent part quality and desired material properties is challenging due to intricate processing parameters and potential process defects such as dynamic melt-pool behavior and localized heat accumulation.This paper reviews recent advances in on-line quality control,focusing on in-situ measurement and closed-loop control for efficient assurance of LDED-fabricated parts.The quality principles,encompassing accuracy and material performance,are summarized to lay a foundation for understanding the mechanisms of quality defects and influencing factors.This review explores and thoroughly compares advancements in indirect process measurements,such as optical,thermal,and acoustic monitoring with direct quality measurements,including laser-line scanning and operando synchrotron X-ray imaging.Depending on the sensing techniques,this paper highlights a hierarchical control strategy for adaptive parameter regulation on intra-layer and inter-layer scales.The requirements and performance of various state-of-the-art controllers are critically compared to indicate their suitable applications.The importance of machine learning in detecting process anomalies and predicting build quality based on sensory signals is also outlined.Future directions are proposed towards adaptive,automated,and intelligent quality control,with a focus on multi-modal monitoring,physics-informed neural networks for interpretable analysis,and multi-objective control applications.展开更多
The direct torque control theory has achieved great success in the control ofinduction motors. However, in the DTC drive system of Permanent Magnet Synchronous Machine (PMSM)proposed a few years ago, there are many ba...The direct torque control theory has achieved great success in the control ofinduction motors. However, in the DTC drive system of Permanent Magnet Synchronous Machine (PMSM)proposed a few years ago, there are many basic theoretical problems that must be clarified. Thispaper describes an investigation about the effect of the zero voltage space vectors in the DTCsystem of PMSM and points out that if using the zero voltage space vectors rationally, not only canthe DTC system be driven successfully but also the torque ripple is reduced and the performance ofthe system is improved. This paper also studies the sensorless technique in the DTC system of PMSMand configures the DTC system of PMSM with sensorless technique including zero voltage spacevectors. Numerical simulations and experimental tests have proved the theory correct. In thecondition of sensor-less, the DTC system of PMSM is wide-rangely speed adjusting, and the ratio ofspeed adjustment is 1: 100.展开更多
This paper proposes a new adaptive iterative learning control approach for a class of nonlinearly parameterized systems with unknown time-varying delay and unknown control direction.By employing the parameter separati...This paper proposes a new adaptive iterative learning control approach for a class of nonlinearly parameterized systems with unknown time-varying delay and unknown control direction.By employing the parameter separation technique and signal replacement mechanism,the approach can overcome unknown time-varying parameters and unknown time-varying delay of the nonlinear systems.By incorporating a Nussbaum-type function,the proposed approach can deal with the unknown control direction of the nonlinear systems.Based on a Lyapunov-Krasovskii-like composite energy function,the convergence of tracking error sequence is achieved in the iteration domain.Finally,two simulation examples are provided to illustrate the feasibility of the proposed control method.展开更多
For a distributed drive electric vehicle(DDEV)driven by four in-wheel motors,advanced vehicle dynamic control methods can be realized easily because motors can be controlled independently,quickly and precisely.And dir...For a distributed drive electric vehicle(DDEV)driven by four in-wheel motors,advanced vehicle dynamic control methods can be realized easily because motors can be controlled independently,quickly and precisely.And direct yaw-moment control(DYC)has been widely studied and applied to vehicle stability control.Good vehicle handling performance:quick yaw rate transient response,small overshoot,high steady yaw rate gain,etc,is required by drivers under normal conditions,which is less concerned,however.Based on the hierarchical control methodology,a novel control system using direct yaw moment control for improving handling performance of a distributed drive electric vehicle especially under normal driving conditions has been proposed.The upper-loop control system consists of two parts:a state feedback controller,which aims to realize the ideal transient response of yaw rate,with a vehicle sideslip angle observer;and a steering wheel angle feedforward controller designed to achieve a desired yaw rate steady gain.Under the restriction of the effect of poles and zeros in the closed-loop transfer function on the system response and the capacity of in-wheel motors,the integrated time and absolute error(ITAE)function is utilized as the cost function in the optimal control to calculate the ideal eigen frequency and damper coefficient of the system and obtain optimal feedback matrix and feedforward matrix.Simulations and experiments with a DDEV under multiple maneuvers are carried out and show the effectiveness of the proposed method:yaw rate rising time is reduced,steady yaw rate gain is increased,vehicle steering characteristic is close to neutral steer and drivers burdens are also reduced.The control system improves vehicle handling performance under normal conditions in both transient and steady response.State feedback control instead of model following control is introduced in the control system so that the sense of control intervention to drivers is relieved.展开更多
Field trials on a silt-loamy paddy soil derived from shallow-sea deposit in direct seeding rice fields were conducted in Zhejiang, China, in 1996 to compare N efficiency of controlled release fertilizers (LP fertilize...Field trials on a silt-loamy paddy soil derived from shallow-sea deposit in direct seeding rice fields were conducted in Zhejiang, China, in 1996 to compare N efficiency of controlled release fertilizers (LP fertilizers) with the conventional urea. Six treatments including CK (no N fertilizer), conventional urea and different types of LP fertilizers at different rates were designed for two succeeding crops of early and late rice. A blend of different types of LP fertilizers as a single preplant "co-situs" application released N in a rate and amount synchronizing with uptake pattern of direct seeding rice. A single preplant application of the LP fertilizers could meet the N requirement of rice for the whole growth period without need of topdressing. Using LP fertilizer blends, equivalent grain yields could be maintained even if the N fertilization rates were reduced by 25%～50% compared with the conventional urea. Agronomic efficiency of the LP fertilizers was 13.6%～ 86.4% higher than that of the conventional urea in early rice and 100%～164.1% in late rice, depending on the amounts of the LP fertilizers applied. N fertilizer recovery rate increased from 27.4% for the conventional application of urea to 41.7%～54.l% for the single preplant "co-situs" application of the LP fertilizers. Use of the LP fertilizers was promising if the increase in production costs due to the high LP fertilizer prices could be compensated by increase in yield and N efficiency, reduction in labor costs and improvement in environment.展开更多
This study presents an improved data-driven Model-Free Adaptive Control(MFAC)strategy for attitude stabilization of a partially constrained combined spacecraft with external disturbances and input saturation. First, a...This study presents an improved data-driven Model-Free Adaptive Control(MFAC)strategy for attitude stabilization of a partially constrained combined spacecraft with external disturbances and input saturation. First, a novel dynamic linearization data model for the partially constrained combined spacecraft with external disturbances is established. The generalized disturbances composed of external disturbances and dynamic linearization errors are then reconstructed by a Discrete Extended State Observer(DESO). With the dynamic linearization data model and reconstructed information, a DESO-MFAC strategy for the combined spacecraft is proposed based only on input and output data. Next, the input saturation is overcome by introducing an antiwindup compensator. Finally, numerical simulations are carried out to demonstrate the effectiveness and feasibility of the proposed controller when the dynamic properties of the partially constrained combined spacecraft are completely unknown.展开更多
Due to growing concerns regarding climate change and environmental protection,smart power generation has become essential for the economical and safe operation of both conventional thermal power plants and sustainable...Due to growing concerns regarding climate change and environmental protection,smart power generation has become essential for the economical and safe operation of both conventional thermal power plants and sustainable energy.Traditional first-principle model-based methods are becoming insufficient when faced with the ever-growing system scale and its various uncertainties.The burgeoning era of machine learning(ML)and data-driven control(DDC)techniques promises an improved alternative to these outdated methods.This paper reviews typical applications of ML and DDC at the level of monitoring,control,optimization,and fault detection of power generation systems,with a particular focus on uncovering how these methods can function in evaluating,counteracting,or withstanding the effects of the associated uncertainties.A holistic view is provided on the control techniques of smart power generation,from the regulation level to the planning level.The benefits of ML and DDC techniques are accordingly interpreted in terms of visibility,maneuverability,flexibility,profitability,and safety(abbreviated as the“5-TYs”),respectively.Finally,an outlook on future research and applications is presented.展开更多
Neural networks require a lot of training to understand the model of a plant or a process. Issues such as learning speed, stability, and weight convergence remain as areas of research and comparison of many training a...Neural networks require a lot of training to understand the model of a plant or a process. Issues such as learning speed, stability, and weight convergence remain as areas of research and comparison of many training algorithms. The application of neural networks to control interior permanent magnet synchronous motor using direct torque control （DTC） is discussed. A neural network is used to emulate the state selector of the DTC. The neural networks used are the back-propagation and radial basis function. To reduce the training patterns and increase the execution speed of the training process, the inputs of switching table are converted to digital signals, i.e., one bit represent the flux error, one bit the torque error, and three bits the region of stator flux. Computer simulations of the motor and neural-network system using the two approaches are presented and compared. Discussions about the back-propagation and radial basis function as the most promising training techniques are presented, giving its advantages and disadvantages. The system using back-propagation and radial basis function networks controller has quick parallel speed and high torque response.展开更多
This paper investigates the consensus problem for linear multi-agent systems with the heterogeneous disturbances generated by the Brown motion.Its main contribution is that a control scheme is designed to achieve the ...This paper investigates the consensus problem for linear multi-agent systems with the heterogeneous disturbances generated by the Brown motion.Its main contribution is that a control scheme is designed to achieve the dynamic consensus for the multi-agent systems in directed topology interfered by stochastic noise.In traditional ways,the coupling weights depending on the communication structure are static.A new distributed controller is designed based on Riccati inequalities,while updating the coupling weights associated with the gain matrix by state errors between adjacent agents.By introducing time-varying coupling weights into this novel control law,the state errors between leader and followers asymptotically converge to the minimum value utilizing the local interaction.Through the Lyapunov directed method and It?formula,the stability of the closed-loop system with the proposed control law is analyzed.Two simulation results conducted by the new and traditional schemes are presented to demonstrate the effectiveness and advantage of the developed control method.展开更多
The purpose was to define the control efficiency and safety of 20% cy- halofop-butyl WP on grass weeds in direct seeded rice fields, in order to provide the basis for chemical weeding. This study measured Leptochloa c...The purpose was to define the control efficiency and safety of 20% cy- halofop-butyl WP on grass weeds in direct seeded rice fields, in order to provide the basis for chemical weeding. This study measured Leptochloa chinensis（L.） Nees, Echinoch/oa crusgalli （L.） Beauv and other gramineous weed control efficiency with four concentrations of 20% cyhalofop-dutyl WP and 100 g/L cyhalofop-dutyl EC in direct seeded rice fields, and analyzed the yield-increasing effect and safety of rice. The results showed that 20% cyhalofop-butyl WP had a good control efficiency on grass weeds such as Leptochloa chinensis（L.） Nees, Echinoch/oa crusgalli（L.） Beauv and other grasses. The effective dosage of 90-150 g/hm2 was over 90.7% on Lep- foch/oa chinensis（L.） Nees and the comprehensive control effect of the grass weeds was above 86.7%, which was basically consistent with 100 g/L cyhalofop-dutyl EC. Furthermore, 20% cyhalofop-dutyl WP was high security for direct seeded rice fields. The yield of rice was increased by 10.18%-11.22% after spraying herbicide. There- fore, 20% of cyhalofop-dutyl WP can be used as a special herbicide for controlling Leptochloa chinensis（L.） Beauv in direct seeded rice fields, and has a good applica- tion prospect.展开更多
This study presents analysis, control and comparison of three hybrid approaches for the direct torque control (DTC) of the dual star induction motor (DSIM) drive. Its objective consists of combining three different he...This study presents analysis, control and comparison of three hybrid approaches for the direct torque control (DTC) of the dual star induction motor (DSIM) drive. Its objective consists of combining three different heuristic optimization techniques including PID-PSO, Fuzzy-PSO and GA-PSO to improve the DSIM speed controlled loop behavior. The GA and PSO algorithms are developed and implemented into MATLAB. As a result, fuzzy-PSO is the most appropriate scheme. The main performance of fuzzy-PSO is reducing high torque ripples, improving rise time and avoiding disturbances that affect the drive performance.展开更多
This paper presents a novel five degrees of freedom (DOF) two-wheeled robotic machine (TWRM) that delivers solutions for both industrial and service robotic applications by enlarging the vehicle′s workspace and incre...This paper presents a novel five degrees of freedom (DOF) two-wheeled robotic machine (TWRM) that delivers solutions for both industrial and service robotic applications by enlarging the vehicle′s workspace and increasing its flexibility. Designing a two-wheeled robot with five degrees of freedom creates a high challenge for the control, therefore the modelling and design of such robot should be precise with a uniform distribution of mass over the robot and the actuators. By employing the Lagrangian modelling approach, the TWRM′s mathematical model is derived and simulated in Matlab/Simulink?. For stabilizing the system′s highly nonlinear model, two control approaches were developed and implemented: proportional-integral-derivative (PID) and fuzzy logic control (FLC) strategies. Considering multiple scenarios with different initial conditions, the proposed control strategies′ performance has been assessed.展开更多
基金Natural Science Basic Research Plan in Shaanxi Province of China(2023-JC-QN-0733).
文摘This paper proposes the nonlinear direct data-driven control from theoretical analysis and practical engineering,i.e.,unmanned aerial vehicle(UAV)formation flight system.Firstly,from the theoretical point of view,consider one nonlinear closedloop system with a nonlinear plant and nonlinear feed-forward controller simultaneously.To avoid the complex identification process for that nonlinear plant,a nonlinear direct data-driven control strategy is proposed to design that nonlinear feed-forward controller only through the input-output measured data sequence directly,whose detailed explicit forms are model inverse method and approximated analysis method.Secondly,from the practical point of view,after reviewing the UAV formation flight system,nonlinear direct data-driven control is applied in designing the formation controller,so that the followers can track the leader’s desired trajectory during one small time instant only through solving one data fitting problem.Since most natural phenomena have nonlinear properties,the direct method must be the better one.Corresponding system identification and control algorithms are required to be proposed for those nonlinear systems,and the direct nonlinear controller design is the purpose of this paper.
基金National Natural Science Foundation of China(62373102)Jiangsu Natural Science Foundation(BK20221455)Anhui Provincial Key Research and Development Project(2022i01020013)。
文摘Enhancing the stability and performance of practical control systems in the presence of nonlinearity,time delay,and uncertainty remains a significant challenge.Particularly,a class of strict-feedback nonlinear uncertain systems characterized by unknown control directions and time-varying input delay lacks comprehensive solutions.In this paper,we propose an observerbased adaptive tracking controller to address this gap.Neural networks are utilized to handle uncertainty,and a unique coordinate transformation is employed to untangle the coupling between input delay and unknown control directions.Subsequently,a new auxiliary signal counters the impact of time-varying input delay,while a Nussbaum function is introduced to solve the problem of unknown control directions.The leverage of an advanced dynamic surface control technique avoids the“complexity explosion”and reduces boundary layer errors.Synthesizing these techniques ensures that all the closed-loop signals are semi-globally uniformly ultimately bounded(SGUUB),and the tracking error converges to a small region around the origin by selecting suitable parameters.Simulation examples are provided to demonstrate the feasibility of the proposed approach.
基金Supported by National Natural Science Foundation of China(Grant Nos.52402497,52025121 and 52002066)Young Scientists Project and General Project of Applied Basic Research in Yunnan Province(Grant Nos.202501AT070296,202401AU070196)+1 种基金The Key Laboratory of Modern Agricultural Engineering of Ordinary Colleges and Universities of Education Department of Autonomous Region(Grant No.TDNG2023108)Jiangsu Provincial Achievements Transformation Project(Grant No.BA2018023).
文摘Distributed drive electric vehicles(DDEVs)endow the ability to improve vehicle stability performance through direct yaw-moment control(DYC).However,the nonlinear characteristics pose a great challenge to vehicle dynamics control.For this purpose,this paper studies the DYC through the Takagi-Sugeno(T-S)fuzzy-based model predictive control to deal with the nonlinear challenge.First,a T-S fuzzy-based vehicle dynamics model is established to describe the time-varying tire cornering stiffness and vehicle speeds,and thus the uncertain parameters can be represented by the norm-bounded uncertainties.Then,a robust model predictive control(MPC)is developed to guarantee vehicle handling stability.A feasible solution can be obtained through a set of linear matrix inequalities(LMIs).Finally,the tests are conducted by the Carsim/Simulink joint platform to verify the proposed method.The comparative results show that the proposed strategy can effectively guarantee the vehicle’s lateral stability while handling the nonlinear challenge.
文摘Permanent magnet synchronous motor(PMSM)is widely used in alternating current servo systems as it provides high eficiency,high power density,and a wide speed regulation range.The servo system is placing higher demands on its control performance.The model predictive control(MPC)algorithm is emerging as a potential high-performance motor control algorithm due to its capability of handling multiple-input and multipleoutput variables and imposed constraints.For the MPC used in the PMSM control process,there is a nonlinear disturbance caused by the change of electromagnetic parameters or load disturbance that may lead to a mismatch between the nominal model and the controlled object,which causes the prediction error and thus affects the dynamic stability of the control system.This paper proposes a data-driven MPC strategy in which the historical data in an appropriate range are utilized to eliminate the impact of parameter mismatch and further improve the control performance.The stability of the proposed algorithm is proved as the simulation demonstrates the feasibility.Compared with the classical MPC strategy,the superiority of the algorithm has also been verified.
基金supported by Postgraduate Research&Practice Innovation Program of Jiangsu Province under Grant KYCX22_0290.
文摘The ability of cyborg locusts to achieve directional movement in complex outdoor environments is critical for search and rescue missions.Currently,there is a lack of research on motion control for cyborg locusts in outdoor settings.In this study,we developed cyborg locusts capable of performing directional locomotion in intricate outdoor environments,including jumping over obstacles,climbing slopes,traversing narrow pipelines,and accurately reaching predetermined targets along specified routes.We designed a miniature electrical backpack(10 mm×10 mm,0.75 g)capable of receiving stimulus parameters(frequency,duty ratio,and stimulation time)via Bluetooth commands from mobile phones.Electrical stimulation of locust sensory organs,such as the antennae and cercus,induced turning and jumping behaviors.Experi-mental testing of locust movement control was conducted under outdoor conditions with a short electrical stimulation interval.Results showed a positive correlation between locust turning angles and electrical stimulation parameters within a specified range,with an average jumping height exceeding 10 cm.Additionally,the success rate of locust turning and jumping behaviors correlated positively with the interval time between electrical stimulations.Adjusting these intervals during forward crawling phases increased the likelihood of the locusts jumping again.In conclusion,this study success-fully achieved directional locomotion control of cyborg locusts outdoors,providing insights and references for advancing search and rescue capabilities.
基金Project(52476095)supported by the National Natural Science Foundation of ChinaProject(kq2506013)supported by Changsha Outstanding Innovative Youth Training Program,China。
文摘The nanofluid-based direct absorption solar collector(NDASC)ensures that solar radiation passing through the tube wall is directly absorbed by the nanofluid,reducing thermal resistance in the energy transfer process.However,further exploration is required to suppress the outward thermal losses from the nanofluid at high temperatures.Herein,this paper proposes a novel NDASC in which the outer surface of the collector tube is covered with functional coatings and a three-dimensional computational fluid dynamics model is established to study the energy flow distributions on the collector within the temperature range of 400-600 K.When the nanofluid’s absorption coefficient reaches 80 m^(-1),the NDASC shows the optimal thermal performance,and the NDASC with local Sn-In_(2)O_(3) coating achieves a 7.8% improvement in thermal efficiency at 400 K compared to the original NDASC.Furthermore,hybrid coatings with Sn In_(2)O_(3)/WTi-Al_(2)O_(3) are explored,and the optimal coverage angles are determined.The NDASC with such coatings shows a 10.22%-17.9% increase in thermal efficiency compared to the original NDASC and a 7.6%-19.5% increase compared to the traditional surface-type solar collectors,demonstrating the effectiveness of the proposed energy flow control strategy for DASCs.
基金supported by the National Natural Science Foundation of China(No.52372371)the Science Center for Gas Turbine Project,China(Nos.P2022-B-V-002-001,P2022-B-V-001-001).
文摘Direct Thrust Control(DTC) is effective in dealing with the mismatch between thrust and rotor speed in traditional engine control. Among the DTC architecture, model-based thrust estimation method has less arithmetic consumption and better real-time performance. In this paper,a direct thrust controller design approach for gas turbine engine based on parameter dependent model is proposed. In order to ensure the stability of DTC control system based on parameter dependent model, there are usually conservatism detects. For the purpose of reducing the conservatism in the solution process of filter and controller, an Equilibrium Manifold Expansion(EME) model with bounded parameter variation of engine is established. The design conditions of Kalman filter for discrete-time EME system are introduced, and the proposed conditions have a certain suppression effect on the input noise of the system with bounded parameter variation.The engine thrust estimator stability and H∞filtering problems are solved by the polytopic quadratic Lyapunov function based on the Linear Matrix Inequalities(LMIs). To meet the performance requirements of thrust control, the Grey Wolf Optimization(GWO) algorithm is applied to optimize the PID control parameters. The proposed method is verified on a Hardware-in-Loop(HIL) platform. The simulation results demonstrate that the DTC framework can ensure the stability of engine closed-loop system in large range deviation tests. The filter and controller solution method considering the parameter variation boundary can obtain a solution that makes the system have better performance parameters. Moreover, the proposed filter has better thrust estimation performance than the traditional Kalman filter under the condition of sensor noise. Compared with Augmented Linear Quadratic Regulator(ALQR) controller, the PID controller optimized by GWO has a faster response in simulation.
基金supported by Royal Academy of Engineering(IF2223B-125)Royal Society(IECR3213107)。
文摘Laser directed energy deposition(LDED)is an emerging branch of metal-based additive manufacturing(AM)processes,offering unprecedented capabilities for high-performance fabrication with complex geometries and near-net shapes.This technology is gathering increasing attention from industries such as biomedical,automotive,and aerospace.However,achieving consistent part quality and desired material properties is challenging due to intricate processing parameters and potential process defects such as dynamic melt-pool behavior and localized heat accumulation.This paper reviews recent advances in on-line quality control,focusing on in-situ measurement and closed-loop control for efficient assurance of LDED-fabricated parts.The quality principles,encompassing accuracy and material performance,are summarized to lay a foundation for understanding the mechanisms of quality defects and influencing factors.This review explores and thoroughly compares advancements in indirect process measurements,such as optical,thermal,and acoustic monitoring with direct quality measurements,including laser-line scanning and operando synchrotron X-ray imaging.Depending on the sensing techniques,this paper highlights a hierarchical control strategy for adaptive parameter regulation on intra-layer and inter-layer scales.The requirements and performance of various state-of-the-art controllers are critically compared to indicate their suitable applications.The importance of machine learning in detecting process anomalies and predicting build quality based on sensory signals is also outlined.Future directions are proposed towards adaptive,automated,and intelligent quality control,with a focus on multi-modal monitoring,physics-informed neural networks for interpretable analysis,and multi-objective control applications.
基金Aeronautical Science Emphasis foundation of China( 98Z5 2 0 0 1) Delta Power Electronics Science &Education DevelopmentF und
文摘The direct torque control theory has achieved great success in the control ofinduction motors. However, in the DTC drive system of Permanent Magnet Synchronous Machine (PMSM)proposed a few years ago, there are many basic theoretical problems that must be clarified. Thispaper describes an investigation about the effect of the zero voltage space vectors in the DTCsystem of PMSM and points out that if using the zero voltage space vectors rationally, not only canthe DTC system be driven successfully but also the torque ripple is reduced and the performance ofthe system is improved. This paper also studies the sensorless technique in the DTC system of PMSMand configures the DTC system of PMSM with sensorless technique including zero voltage spacevectors. Numerical simulations and experimental tests have proved the theory correct. In thecondition of sensor-less, the DTC system of PMSM is wide-rangely speed adjusting, and the ratio ofspeed adjustment is 1: 100.
基金supported by National Natural Science Foundation of China (No. 60974139)Fundamental Research Funds for the Central Universities (No. 72103676)
文摘This paper proposes a new adaptive iterative learning control approach for a class of nonlinearly parameterized systems with unknown time-varying delay and unknown control direction.By employing the parameter separation technique and signal replacement mechanism,the approach can overcome unknown time-varying parameters and unknown time-varying delay of the nonlinear systems.By incorporating a Nussbaum-type function,the proposed approach can deal with the unknown control direction of the nonlinear systems.Based on a Lyapunov-Krasovskii-like composite energy function,the convergence of tracking error sequence is achieved in the iteration domain.Finally,two simulation examples are provided to illustrate the feasibility of the proposed control method.
基金Supported by National Basic Research Program of China(973 Program,Grant No.2011CB711200)National Science and Technology Support Program of China(Grant No.2015BAG17B00)National Natural Science Foundation of China(Grant No.51475333)
文摘For a distributed drive electric vehicle(DDEV)driven by four in-wheel motors,advanced vehicle dynamic control methods can be realized easily because motors can be controlled independently,quickly and precisely.And direct yaw-moment control(DYC)has been widely studied and applied to vehicle stability control.Good vehicle handling performance:quick yaw rate transient response,small overshoot,high steady yaw rate gain,etc,is required by drivers under normal conditions,which is less concerned,however.Based on the hierarchical control methodology,a novel control system using direct yaw moment control for improving handling performance of a distributed drive electric vehicle especially under normal driving conditions has been proposed.The upper-loop control system consists of two parts:a state feedback controller,which aims to realize the ideal transient response of yaw rate,with a vehicle sideslip angle observer;and a steering wheel angle feedforward controller designed to achieve a desired yaw rate steady gain.Under the restriction of the effect of poles and zeros in the closed-loop transfer function on the system response and the capacity of in-wheel motors,the integrated time and absolute error(ITAE)function is utilized as the cost function in the optimal control to calculate the ideal eigen frequency and damper coefficient of the system and obtain optimal feedback matrix and feedforward matrix.Simulations and experiments with a DDEV under multiple maneuvers are carried out and show the effectiveness of the proposed method:yaw rate rising time is reduced,steady yaw rate gain is increased,vehicle steering characteristic is close to neutral steer and drivers burdens are also reduced.The control system improves vehicle handling performance under normal conditions in both transient and steady response.State feedback control instead of model following control is introduced in the control system so that the sense of control intervention to drivers is relieved.
文摘Field trials on a silt-loamy paddy soil derived from shallow-sea deposit in direct seeding rice fields were conducted in Zhejiang, China, in 1996 to compare N efficiency of controlled release fertilizers (LP fertilizers) with the conventional urea. Six treatments including CK (no N fertilizer), conventional urea and different types of LP fertilizers at different rates were designed for two succeeding crops of early and late rice. A blend of different types of LP fertilizers as a single preplant "co-situs" application released N in a rate and amount synchronizing with uptake pattern of direct seeding rice. A single preplant application of the LP fertilizers could meet the N requirement of rice for the whole growth period without need of topdressing. Using LP fertilizer blends, equivalent grain yields could be maintained even if the N fertilization rates were reduced by 25%～50% compared with the conventional urea. Agronomic efficiency of the LP fertilizers was 13.6%～ 86.4% higher than that of the conventional urea in early rice and 100%～164.1% in late rice, depending on the amounts of the LP fertilizers applied. N fertilizer recovery rate increased from 27.4% for the conventional application of urea to 41.7%～54.l% for the single preplant "co-situs" application of the LP fertilizers. Use of the LP fertilizers was promising if the increase in production costs due to the high LP fertilizer prices could be compensated by increase in yield and N efficiency, reduction in labor costs and improvement in environment.
基金supported by National Natural Science Foundation of China(Nos.61603114,61673135)the Fundamental Research Funds for the Central Universities of China(No.HIT.NSRIF.201826)
文摘This study presents an improved data-driven Model-Free Adaptive Control(MFAC)strategy for attitude stabilization of a partially constrained combined spacecraft with external disturbances and input saturation. First, a novel dynamic linearization data model for the partially constrained combined spacecraft with external disturbances is established. The generalized disturbances composed of external disturbances and dynamic linearization errors are then reconstructed by a Discrete Extended State Observer(DESO). With the dynamic linearization data model and reconstructed information, a DESO-MFAC strategy for the combined spacecraft is proposed based only on input and output data. Next, the input saturation is overcome by introducing an antiwindup compensator. Finally, numerical simulations are carried out to demonstrate the effectiveness and feasibility of the proposed controller when the dynamic properties of the partially constrained combined spacecraft are completely unknown.
文摘Due to growing concerns regarding climate change and environmental protection,smart power generation has become essential for the economical and safe operation of both conventional thermal power plants and sustainable energy.Traditional first-principle model-based methods are becoming insufficient when faced with the ever-growing system scale and its various uncertainties.The burgeoning era of machine learning(ML)and data-driven control(DDC)techniques promises an improved alternative to these outdated methods.This paper reviews typical applications of ML and DDC at the level of monitoring,control,optimization,and fault detection of power generation systems,with a particular focus on uncovering how these methods can function in evaluating,counteracting,or withstanding the effects of the associated uncertainties.A holistic view is provided on the control techniques of smart power generation,from the regulation level to the planning level.The benefits of ML and DDC techniques are accordingly interpreted in terms of visibility,maneuverability,flexibility,profitability,and safety(abbreviated as the“5-TYs”),respectively.Finally,an outlook on future research and applications is presented.
基金the National Natural Science Foundation of China (60374032).
文摘Neural networks require a lot of training to understand the model of a plant or a process. Issues such as learning speed, stability, and weight convergence remain as areas of research and comparison of many training algorithms. The application of neural networks to control interior permanent magnet synchronous motor using direct torque control （DTC） is discussed. A neural network is used to emulate the state selector of the DTC. The neural networks used are the back-propagation and radial basis function. To reduce the training patterns and increase the execution speed of the training process, the inputs of switching table are converted to digital signals, i.e., one bit represent the flux error, one bit the torque error, and three bits the region of stator flux. Computer simulations of the motor and neural-network system using the two approaches are presented and compared. Discussions about the back-propagation and radial basis function as the most promising training techniques are presented, giving its advantages and disadvantages. The system using back-propagation and radial basis function networks controller has quick parallel speed and high torque response.
基金supported in part by the National Natural Science Foundation of China(61722312,61533017,62073321)the National Key Research and Development Program of China(2018YFB1702300)。
文摘This paper investigates the consensus problem for linear multi-agent systems with the heterogeneous disturbances generated by the Brown motion.Its main contribution is that a control scheme is designed to achieve the dynamic consensus for the multi-agent systems in directed topology interfered by stochastic noise.In traditional ways,the coupling weights depending on the communication structure are static.A new distributed controller is designed based on Riccati inequalities,while updating the coupling weights associated with the gain matrix by state errors between adjacent agents.By introducing time-varying coupling weights into this novel control law,the state errors between leader and followers asymptotically converge to the minimum value utilizing the local interaction.Through the Lyapunov directed method and It?formula,the stability of the closed-loop system with the proposed control law is analyzed.Two simulation results conducted by the new and traditional schemes are presented to demonstrate the effectiveness and advantage of the developed control method.
基金Supported by Natural Science Foundation of Hunan Province(12JJ6026)Innovation Platform in Higher Educational Institutions of Hunan Province(14K053)Hunan Province Higher Educational Institutions Industrialization Program(13CY030)~~
文摘The purpose was to define the control efficiency and safety of 20% cy- halofop-butyl WP on grass weeds in direct seeded rice fields, in order to provide the basis for chemical weeding. This study measured Leptochloa chinensis（L.） Nees, Echinoch/oa crusgalli （L.） Beauv and other gramineous weed control efficiency with four concentrations of 20% cyhalofop-dutyl WP and 100 g/L cyhalofop-dutyl EC in direct seeded rice fields, and analyzed the yield-increasing effect and safety of rice. The results showed that 20% cyhalofop-butyl WP had a good control efficiency on grass weeds such as Leptochloa chinensis（L.） Nees, Echinoch/oa crusgalli（L.） Beauv and other grasses. The effective dosage of 90-150 g/hm2 was over 90.7% on Lep- foch/oa chinensis（L.） Nees and the comprehensive control effect of the grass weeds was above 86.7%, which was basically consistent with 100 g/L cyhalofop-dutyl EC. Furthermore, 20% cyhalofop-dutyl WP was high security for direct seeded rice fields. The yield of rice was increased by 10.18%-11.22% after spraying herbicide. There- fore, 20% of cyhalofop-dutyl WP can be used as a special herbicide for controlling Leptochloa chinensis（L.） Beauv in direct seeded rice fields, and has a good applica- tion prospect.
基金Project supported by Faculty of Technology,Department of Electrical Engineering,University of Batna,Algeria
文摘This study presents analysis, control and comparison of three hybrid approaches for the direct torque control (DTC) of the dual star induction motor (DSIM) drive. Its objective consists of combining three different heuristic optimization techniques including PID-PSO, Fuzzy-PSO and GA-PSO to improve the DSIM speed controlled loop behavior. The GA and PSO algorithms are developed and implemented into MATLAB. As a result, fuzzy-PSO is the most appropriate scheme. The main performance of fuzzy-PSO is reducing high torque ripples, improving rise time and avoiding disturbances that affect the drive performance.
文摘This paper presents a novel five degrees of freedom (DOF) two-wheeled robotic machine (TWRM) that delivers solutions for both industrial and service robotic applications by enlarging the vehicle′s workspace and increasing its flexibility. Designing a two-wheeled robot with five degrees of freedom creates a high challenge for the control, therefore the modelling and design of such robot should be precise with a uniform distribution of mass over the robot and the actuators. By employing the Lagrangian modelling approach, the TWRM′s mathematical model is derived and simulated in Matlab/Simulink?. For stabilizing the system′s highly nonlinear model, two control approaches were developed and implemented: proportional-integral-derivative (PID) and fuzzy logic control (FLC) strategies. Considering multiple scenarios with different initial conditions, the proposed control strategies′ performance has been assessed.
